Assessing quality of health services with the SERVQUAL model in Iran. A systematic review and meta-analysis - Chuyên Trang Chia Sẻ Kiến Thức Thời Trang Mới Nhất

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Abstract

Purpose

The five-dimension service quality (SERVQUAL) scale is one of the most common tools for evaluating gaps between clients’ perceptions and expectations. This study aimed to assess the quality of health services in Iran through a meta-analysis of all Iranian studies which used the SERVQUAL tool.

Data sources

A systematic literature review has been performed in Web of Science, PubMed, Scopus, Google Scholar, Iran Medex, Magiran and Scientific Information Database.

Study selection

All relevant English or Persian studies published between January 2009 and April 2016 were have been selected. Papers were considered if they regarded all five dimensions of the SERVQUAL tool for assessing the quality of health care services.

Data extraction

Two reviewer independently extracted mean and standard deviation of five dimensions and characteristics of studies. The quality of studies included in meta-analysis using STROBE checklist.

Results of data synthesis

Of 315 studies initially identified, 12 were included in our meta-analysis. All analyses were performed in Stata MP v. 14. Patients’ perceptions were lower than their expectations (gap = −1.64). Responsibility (−1.22) and reliability (−1.15) had the lowest gaps, and tangibility and empathy (−1.03) had the largest gaps. Except gender, other variables had no significant associations with gaps. Patients in the cities of Arak (−3.47) and Shiraz (−3.02) had the largest gaps.

Conclusions

All dimensions of service quality were negative, which implies that the quality of health services in Iran has not been satisfying to patients and needs to be improved.

Introduction

Quality is a prominent concept in real life, and can inform efforts to develop effective strategies to improve service systems [1]. In the health sector, the value of services and their relation with people’s lives, quality assurance and quality promotion have received growing attention; moreover, taxpayers have increasing expectations from hospitals and other organisms that provide health care [2]. Providing high-quality services is of key importance in the management of service organizations. Hospitals in particular aim to provide excellent clinical care and quality services to their patients. Furthermore, raising the quality of health care services is associated with an increase in profits, cost savings and market share [3].

Service quality comprises two elements: (i) technical quality, based on the results of the service encounter and (ii) functional quality, which is focused on the internal procedures involved in providing a service. The SERVQUAL model is structured on functional quality rather than technical quality [4], and on the veracity of medical diagnoses and procedures [5]. Technical quality also reflects the competence of professionals and laboratory technicians’ expertise in conducting tests [6]. Patients’ expectations need to be considered in health service delivery because information about this can not only help ensure that medical procedures are effective from the experts’ viewpoint, but can also help attain goals in functional quality [2]. Client’ perceptions of service quality result from a comparison of their before-service expectations with their actual service experience. Based on this perspective, Parasuraman et al. developed a scale for measuring service quality, which is mostly popular known as SERVQUAL [7]. Parasuraman defined service quality as the difference between Client’ expectations and Client’ perceptions. When expectations are greater than perceptions a service quality gap exists [8]. The SERVQUAL tool determines the relative influence of five dimensions, namely tangibility, reliability, responsibility, assurance and empathy, on customer perceptions, and can be used to track quality trends over time [9].

Five dimensions of service quality that are applicable to service-providing organizations in general [10]: (i) tangibles, i.e. physical facilities, equipment and staff appearance; (ii) reliability, i.e. the ability to perform the promised service dependably and accurately; (iii) assurance, i.e. employees’ knowledge, courtesy and ability to instill trust and confidence in the customer towards the service provider; (iv) responsibility, i.e. the willingness to help customers and provide prompt service; and (v) empathy, i.e. the provision of caring, individualized attention to customers [11, 12]. The SERVQUAL scale consists of 44 questions to analyze the gap between expectations and perceptions. The first 22 questions are related to customer expectations, and the second set of 22 items is related to customer perceptions of their service consumption [13]. Responses to each items or question are indicated on a 5-point scale [14]. For each question, the gap between the client’s perceptions and expectations is calculated as the perceptions score minus the expectations score (P – E) [13].

The SERVQUAL model has been applied in several countries to measure service quality in hospitals and health services in (for example) Romania [6], Turkey [15], Saudi Arabia [16], Bangladesh [17] and Iran, where it has been used to evaluate perceptions of service quality by medical university students [18–23] and by patients at hospitals, primary health care centers and other health centers [2, 5, 24–40]. Many studies in Iran have investigated service quality in the health sector, but to our knowledge the data from these publications has not been used in a meta-analysis of this research. Therefore, the aim of this study was to perform a meta-analysis to combine the findings of comparable studies in order to identify consistencies and contradictions in the available evidence.

Methods

Search method

The electronic databases for medical publications Web of Sciences, PubMed, Scopus, Google Scholar, Magiran, Iran Medex and Scientific Information Database (SID) were searched for articles published in English or Persian from January 2009 to April 2016. The databases were searched with original search queries containing the terms ‘service quality’, ‘SERVQUAL’, ‘health quality’, ‘patients’ expectation’, ‘patients’ perception’, ‘expectation’, ‘perception’, ‘health care services’ and ‘Iran’ in combination using ‘AND’ and ‘OR’.

Study selection

To select appropriate studies, two reviewers scrutinized titles and abstracts of all studies returned by the search strategy. Then they independently evaluated the full text of potentially relevant non-duplicated articles. Any disagreement was resolved by discussion between the two reviewers. When no agreement was reached, a third reviewer was consulted. The kappa index to determine the degree of agreement between two reviewers was 79%, indicating a high level of agreement.

We also used the 22-item STROBE checklist (https://strobe-statement.org) to assess the quality of studies in this meta-analysis. A score between 0 and 7 was considered low quality, 8 and 17 as moderate, and 18 and 22 as high quality.

Inclusion/exclusion criteria and data extraction

All cross-sectional studies that met the following criteria were included: conducted in Iran, sample size >90 participants, all five dimensions of the SERVQUAL tool used to assess the quality of health care services, standardized mean differences (SMD) and standard error (SE) reported. We extracted the mean and standard deviation (SD) for each dimension of the SERVQUAL questionnaire, publication year, location of the study (city), sample size, type of study, age, gender and marital status of participations from each study.

Outcome measures

The SMD was the main variable used for analysis in this study. It was calculated as patients’ perception minus patients’ expectation for all items in all five dimensions (tangibility, reliability, responsibility, assurance and empathy).

Statistical analysis

D. The SD values were calculated with the following formula:

SED=sExp2+sPerc2−2sExpsPercrExp,Percn

ExpPerc = 0.5 [

]. Cochran’s heterogeneity statistic (P < 0.1) and the I-squared index (25% low; 50% medium; 75%, high) were used to evaluate the magnitude of heterogeneity among the true effect sizes [

]. A forest plot was generated with the results for ES values, with 95% confidence intervals (95% CI). Subgroup analysis and meta-regression were used to evaluate the association between calculated SMDs and characteristics such as year of publication, gender, age, marital status and location (city) of the study. Potential publication bias was explored with Egger’s test, and the trim-and-fill technique was used to adjust the pooled estimates for the likelihood of missing studies [

]. All statistical analyses were done with the Stata MP Statistical Software Package, version 14.

The SMD (Hedges’ g) was used as the effect size for all health care services in the studies included in our analysis. Then SMD was obtained as the mean difference divided by SE. The SD values were calculated with the following formula:where, it is assumed that the correlation (r) between expectations and perceptions is r= 0.5 [ 41 ]. Cochran’s heterogeneity statistic (P < 0.1) and the I-squared index (25% low; 50% medium; 75%, high) were used to evaluate the magnitude of heterogeneity among the true effect sizes [ 42 ]. A forest plot was generated with the results for ES values, with 95% confidence intervals (95% CI). Subgroup analysis and meta-regression were used to evaluate the association between calculated SMDs and characteristics such as year of publication, gender, age, marital status and location (city) of the study. Potential publication bias was explored with Egger’s test, and the trim-and-fill technique was used to adjust the pooled estimates for the likelihood of missing studies [ 43 ]. All statistical analyses were done with the Stata MP Statistical Software Package, version 14.

Results

A total of 59 studies were identified and subjected to initial screening. We then selected 38 articles provisionally for further full-text evaluation. After this step 12 studies [35, 39, 44–53] were found to meet our inclusion criteria (Fig. 1). According to the STROBE checklist these studies obtained a mean score of 19, indicating that the quality of included studies in this meta-analysis was high.

Figure 1

PRISMA flowchart describing the study design. Open in new tabDownload slide

PRISMA flowchart describing the study design.

A total of 20 cross-sectional studies were included in this meta-analysis. The total number of participants was 3060 (range from 96 to 400 in individual reports), and 57.4% of them were men. Most men were married (75.90%), with a mean age of 37 years. Six studies (50%) were published in English (Table 1). The cities of Shiraz and Arak had the largest gaps between patients’ expectations and perceptions, and Zabol had the smallest gap (Fig. 2).

Table 1

Ref. no.

Year

Language

Location

Sample size

Male (%)

Age (mean)

Married (%)

[

49] 2009 Persian Zanjan 300 NR 28.40 NR [

48] 2011 Persian Neyshabur 400 NR 32.54 NR [

47] 2012 Persian Arak 260 46.20 39.89 84.60 [

35] 2013 Persian Urmia 390 NR 29.80 NR [

50] 2013 Persian Zabol 100 55 NR 93 [

44] 2014 English Kerman 195 59.20 NR 63.60 [

45] 2014 English Kerman 260 88.70 37 71.50 [

46] 2014 English Bandar Abbas 96 64 NR NR [

51] 2015 Persian Isfahan 104 55.80 NR 76 [

52] 2016 English Kermanshah 400 63 38.5 69.30 [

53] 2016 English Shiraz 300 64 49.66 77 [

39] 2016 English Khuzestan 255 21 40 80 Total – – – 3060 37.32 76.78 Ref. no.

Year

Language

Location

Sample size

Male (%)

Age (mean)

Married (%)

[

49] 2009 Persian Zanjan 300 NR 28.40 NR [

48] 2011 Persian Neyshabur 400 NR 32.54 NR [

47] 2012 Persian Arak 260 46.20 39.89 84.60 [

35] 2013 Persian Urmia 390 NR 29.80 NR [

50] 2013 Persian Zabol 100 55 NR 93 [

44] 2014 English Kerman 195 59.20 NR 63.60 [

45] 2014 English Kerman 260 88.70 37 71.50 [

46] 2014 English Bandar Abbas 96 64 NR NR [

51] 2015 Persian Isfahan 104 55.80 NR 76 [

52] 2016 English Kermanshah 400 63 38.5 69.30 [

53] 2016 English Shiraz 300 64 49.66 77 [

39] 2016 English Khuzestan 255 21 40 80 Total – – – 3060 37.32 76.78
Open in new tab

Table 1

Ref. no.

Year

Language

Location

Sample size

Male (%)

Age (mean)

Married (%)

[

49] 2009 Persian Zanjan 300 NR 28.40 NR [

48] 2011 Persian Neyshabur 400 NR 32.54 NR [

47] 2012 Persian Arak 260 46.20 39.89 84.60 [

35] 2013 Persian Urmia 390 NR 29.80 NR [

50] 2013 Persian Zabol 100 55 NR 93 [

44] 2014 English Kerman 195 59.20 NR 63.60 [

45] 2014 English Kerman 260 88.70 37 71.50 [

46] 2014 English Bandar Abbas 96 64 NR NR [

51] 2015 Persian Isfahan 104 55.80 NR 76 [

52] 2016 English Kermanshah 400 63 38.5 69.30 [

53] 2016 English Shiraz 300 64 49.66 77 [

39] 2016 English Khuzestan 255 21 40 80 Total – – – 3060 37.32 76.78 Ref. no.

Year

Language

Location

Sample size

Male (%)

Age (mean)

Married (%)

[

49] 2009 Persian Zanjan 300 NR 28.40 NR [

48] 2011 Persian Neyshabur 400 NR 32.54 NR [

47] 2012 Persian Arak 260 46.20 39.89 84.60 [

35] 2013 Persian Urmia 390 NR 29.80 NR [

50] 2013 Persian Zabol 100 55 NR 93 [

44] 2014 English Kerman 195 59.20 NR 63.60 [

45] 2014 English Kerman 260 88.70 37 71.50 [

46] 2014 English Bandar Abbas 96 64 NR NR [

51] 2015 Persian Isfahan 104 55.80 NR 76 [

52] 2016 English Kermanshah 400 63 38.5 69.30 [

53] 2016 English Shiraz 300 64 49.66 77 [

39] 2016 English Khuzestan 255 21 40 80 Total – – – 3060 37.32 76.78
Open in new tab

Figure 2

Graphic representation of SMD (gap between patients’expectation and perception) in each province in Iran. The asterisk (*) indicates that two studies were included. Open in new tabDownload slide

Graphic representation of SMD (gap between patients’expectation and perception) in each province in Iran. The asterisk (*) indicates that two studies were included.

According to random effect meta-analysis (I-squared index 98.9%, P < 0.001) the pooled estimate of SMD was −1.64 (95% CI: −2.21, −1.07), which indicated that the expectations of patients at Iranian hospitals was significantly higher than their perceptions (z = 5.64, P < 0.001). The SMD varied from −3.47 (reported by Hekmatpoor in 2012) to −0.07 (reported by Ajam et al. in 2013) [50] (Fig. 3).

Figure 3

Forest plot for SMD (95%CI) of patients’ perceptions and expectations. Open in new tabDownload slide

Forest plot for SMD (95%CI) of patients’ perceptions and expectations.

Subgroup analyses indicated that there were no significant differences among dimensions of patients’ expectations (z = 0.93, df = 4, P = 0.980) and dimensions of patients’ perceptions (z = 1.13, df = 4, P = 0.920). The largest variations in patients’ expectations were in the assurance and empathy dimensions, and the largest variations in patients’ perceptions were in the empathy and tangibility dimensions (Table 2).

Table 2

Dimension

Patients’ expectation

Patients’ perception

Mean (95%CI)

Tangibility 14 4.64 (4.35, 4.74) 99.5 0.89 3.72 (3.54, 3.89) 99.4 0.920 Reliability 14 4.59 (4.39, 4.79) 99.4 3.77 (3.54, 4.01) 99.7 Responsibility 14 4.66 (4.67, 4.85) 99.4 3.76 (3.49, 4.02) 99.7 Assurance 14 4.67 (4.46, 4.88) 99.4 3.87 (3.81, 4.41) 99.6 Empathy 14 4.51 (4.27, 4.78) 99.2 3.97 (3.64, 3.29) 99.5 Dimension

Patients’ expectation

Patients’ perception

Mean (95%CI)

Table 2

Dimension

Patients’ expectation

Patients’ perception

Mean (95%CI)

Patients’ expectation

Patients’ perception

Mean (95%CI)

The pooled estimated SMD for responsibility and reliability was −1.22 (95% CI: −1.65, −0.78) and −1.15 (95% CI: −1.58, −0.71), respectively. The gap between expectations and perceptions was lowest for empathy [−1.03 (95% CI: −1.42, −0.65)] and tangibility [−1.03 (95% CI: −1.41, −0.64)] (Table 3 and Fig. 4).

Table 3

Dimensions

95% CI

I-squared (%)

Lower

Upper

Tangibility 14 −1.03 −1.42 −0.65 97.9 5.25 <0.001 Reliability 14 −1.15 −1.58 −0.71 98.4 5.14 <0.001 Responsibility 14 −1.22 −1.65 −0.78 98.3 5.47 <0.001 Assurance 14 −1.13 −1.49 −0.78 97.5 6.28 <0.001 Empathy 14 −1.03 −1.41 −0.64 98.0 5.18 <0.001 Dimensions

95% CI

I-squared (%)

Lower

Upper

Table 3

Dimensions

95% CI

I-squared (%)

Lower

Upper

95% CI

I-squared (%)

Lower

Upper

Figure 4

Forest plot of mean differences in quality of health care services in five dimensions. The midpoint in each line indicates the prevalence rate, and the length of each line indicates the 95% confidence interval of each study. Diamonds indicate the 95% confidence interval for each study. Open in new tabDownload slide

The SMD gap was significantly lower in men [−1.29 (95% CI: −2.44, −0.013)] than women [−1.80 (95% CI: −2.50, −1.10)] (P = 0.005) (Table 4).

Table 4

Variables

Coef

Sample −0.003 0.53 1.61 0.107 Gender 0.03 0.01 2.79 0.005 Age 0.03 0.05 −0.54 0.59 Marriage 2.33 8.86 0.26 0.797 Language 0.86 0.53 1.61 0.107 Variables

Coef

Sample −0.003 0.53 1.61 0.107 Gender 0.03 0.01 2.79 0.005 Age 0.03 0.05 −0.54 0.59 Marriage 2.33 8.86 0.26 0.797 Language 0.86 0.53 1.61 0.107
Open in new tab

Table 4

Variables

Coef

Sample −0.003 0.53 1.61 0.107 Gender 0.03 0.01 2.79 0.005 Age 0.03 0.05 −0.54 0.59 Marriage 2.33 8.86 0.26 0.797 Language 0.86 0.53 1.61 0.107 Variables

Coef

Sample −0.003 0.53 1.61 0.107 Gender 0.03 0.01 2.79 0.005 Age 0.03 0.05 −0.54 0.59 Marriage 2.33 8.86 0.26 0.797 Language 0.86 0.53 1.61 0.107
Open in new tab

The funnel plot and results of Egger’s test indicated evidence of publication bias in some studies (z = −0.06, P < 0.001). After trim-and-fill analysis, the estimated SMD was −1.63 (95% CI: −2.11, −1.15). As shown in Fig. 5, there was no difference between these results and the forest plot in Fig. 3.

Figure 5

Begg’s funnel plot of publication bias for mean differences in quality of health care services. Open in new tabDownload slide

Begg’s funnel plot of publication bias for mean differences in quality of health care services.

Discussion

The results of our meta-analysis show that patients’ expectations for quality in health care services in Iran surpassed their perceptions. In all dimensions of service quality as evaluated with the SERVQUAL tool, patients’ perceptions indicated dissatisfaction. Of the five dimensions, responsibility and reliability showed the largest gaps.

Previous studies reported the largest gaps in responsibility [24, 35, 46, 54, 55] or reliability [20, 37, 39, 49, 53, 56–58]. In contrast, however, other studies found the smallest gap in the responsibility [52, 58, 59] or reliability dimension [36, 60]. Responsibility reflects staff members’ ability to solve patients’ problems easily and quickly, provide timely services, provide a clear description of the services to the patients, and reduce patients’ waiting times as much as possible [39]. A negative gap means that customers’ expectations for quality in the responsibility dimension have not been met. Low perceived responsiveness compromises an organization’s ability to achieve patient satisfaction, so if health service providers seek to improve service quality and increase customer satisfaction, staff training in customers’ needs is an essential first step [2]. A negative gap also suggests that health center managers and policy makers should pay more attention to patients’ rights and be more responsive to perceived shortcomings. Accordingly, health service staff members, especially those who are in direct contact with customers, have the greatest impact on service quality; hence, customer satisfaction should receive priority in service quality improvement programs [46]. By providing timely services, managers of health providing centers can improve user satisfaction in the responsibility dimension and decrease their customers’ dissatisfaction [39].

Our findings showed that the smallest gaps between patients’ expectations and perceptions were in the tangibility and empathy dimensions. We interpret this as evidence that managers of these sectors are more attentive to tangibility and empathy, and take measures to ensure appropriate facilities and equipment, as well as employees’ appearance. Some earlier studies found slight differences between customers’ expectations and perceptions in the tangibility dimension [5, 16, 44, 61]. However, other reports found that among the five dimensions, tangibility had the largest gap between expectations and perceptions [2, 6, 39, 62].

A study by Parasuraman et al. showed that the tangibility dimension was not very important from the patients’ viewpoint. Although there is evidence that this is the most important dimension in some specific service environments, in health systems it is overshadowed by other dimensions [49]. Empathy in particular involves dealing with each customer according to their mood, so that customers are convinced that the organization has understood them [37].

In our study empathy yielded the smallest gap between expectations and perceptions, and although this result is consistent with some earlier studies [5, 37, 48, 63], others reported the largest gap for this dimension [36, 40, 44]. A possible explanation for the discrepant results may be the emphasis in Eastern cultures on the quality of communication, which may lead clients’ perceptions to fall short of their expectations. Although the empathy dimension produced a smaller gap than other dimensions, it appears advisable to take measures to improve the relationship between customers and personnel to improve customer satisfaction.

Many studies of service quality have reported gaps between customers’ perceptions and expectations. In Iran some studies found a negative gap for all five dimensions [2, 5, 38, 50, 51, 58, 61, 64, 65]. Ajam et al. found the positive gap in delivered services except assurance and responsibility. They stated that particular type of this service provider (field hospital), free of charges services and the most important that deprived people receiving this hospital services were the reasons of this result [50]. In a survey at a Turkish university hospital, Bakar et al. [66] found that patients’ scores for perceptions were higher than expected for an ordinary hospital but lower than expected for a high-quality hospital. Lin et al. [8], who measured patients’ expectations and perceptions of quality for laser in situ keratomileusis (LASIK) services, found service quality gaps in the reliability, assurance and empathy dimensions. Mangold and Babakus and Babakus and Mangold [10, 67] found quality gaps in all dimensions. The negative gap in all dimensions in the current study showed that the policy makers of health services could not meet the expectation of the customers which was more than their perception in Iran. In the most studies, the expectation and perception of customers in each dimension classified in order of priority from the viewpoint of customers.

A study of Greek NHS hospitals showed that among the three dimensions of service quality, patients seemed to be most satisfied with access, followed by the human aspect and the physical environment and infrastructure dimensions [69]. Al Fraihi et al. [62] found that the empathy dimension contributed most to patients’ expectations and perceptions, and responsibility contributed least. In a private hospital in Tehran, tangibility had the highest expectation and perception scores, whereas empathy had the lowest scores [5].

Our analysis of expectations or perceptions separately disclosed no significant differences among the five dimensions. This finding means that based on customers’ views, all dimensions of service quality are equally important. Therefore, all five service quality dimensions of the SERVQUAL tool appear to be suited for monitoring patients’ expectations and perceptions of service quality at health care centers. An encouraging observation from our cumulative meta-analysis (Fig. 5) is that between 2009 and 2016, the gap between expectation and perception of patients at Iranian hospitals tended to diminish. This trend may reflect increased attention by the Ministry of Health to service quality and the prioritization of customer satisfaction.

Limitations

One of the limitations of this meta-analysis is the small sample size for subgroups such as age, sex and marital status. Although we used meta-regression to overcome this potential weakness, low sample sizes nonetheless limit the generalizability of our findings for specific gaps in different subgroup analyses. Another potential limitation is publication bias, a problem that can distort the estimates we obtained. We noted potential sources of publication bias in the studies we included, probably arising from aspects such as language bias, citation bias, multiple publications, selective outcome reporting, selective reporting, poor methodological design and inadequate data analysis [70].

Conclusions

The gaps we found between mean scores for expectations and perceptions were negative for all five dimensions of the SERVQUAL tool, a finding which implies that patients in Iran are not fully satisfied with the quality of health services. Improvements are needed, and our study thus presents an opportunity to identify areas of strengths and weakness in the quality of health care provided by health organizations in Iran. We believe the present review identifies areas where the need for quality improvement is most urgent, and thus has important implications for health providers in Iran.

Acknowledgements

We thank Mr Alireza Amanollahi, Instructor at the Medical Library and Information Science department and Counselor at the Clinical Research Development Center of Shahid Mohammadi Hospital, for collecting data, and K. Shashok (AuthorAID in the Eastern Mediterranean) for improving the use of English in the article.

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